分析化学2024，Vol.52Issue(7)：985-994,中插22-中插29,18.DOI:10.19756/j.issn.0253-3820.241085
基于预涂纳米碳-十二烷基硫酸钠复合基质的基质辅助激光解吸电离质谱分析与猪脑组织切片质谱成像
Matrix-Assisted Laser Desorption Ionization Mass Spectrometry Analysis and Imaging of Porcine Brain Tissue Section Using Precoated Nanocarbon-Sodium Dodecyl Sulfate Composite Matrix
摘要
Abstract
Nanomaterial matrices have unique advantages in small molecule analysis by matrix-assisted laser desorption ionization mass spectrometry(MALDI-MS).On the basis of comparing different surfactants,a method for pre-coating nanocarbon sodium dodecyl sulfate(SDS)composite matrix was established,which could alleviate the issue of aggregation of nanocarbon particles as a matrix.The experimental results showed that the nanocarbon-SDS composite pre-coated matrix effectively suppressed the background ion peak of the nano matrix,significantly improved the MS peak intensity and signal-to-noise ratio of the tested substance.Under the optimal conditions,cholesterol,1,2-dipalmitoyl-sn-glyceryl-3-phosphorylcholine(DPPC),and triglyceride standards were analyzed,with intra-point repeatability(RSD)of MS peak intensity≤5%and inter-point repeatability≤7%.As to measurement of cyclic adenosine monophosphate and DPPC samples in the range of 0.05‒1.0 mg/mL,linear correlation coefficient(R2)between peak intensity and concentration was greater than 0.993,indicating good quantitative analysis potential.The nanocarbon-SDS composite pre-coating matrix was used for MALDI-MS imaging of pig brain tissue,and the differences in component distribution between pig brain white matter and gray matter were observed,demonstrating the potential of nanocarbon-SDS composite pre-coating matrix for MALDI-MS imaging.关键词
基质辅助激光解吸电离质谱/纳米碳基质/十二烷基硫酸钠/组织切片/质谱成像Key words
Matrix assisted laser desorption ionization mass spectrometry/Nanocarbon matrix/Sodium dodecyl sulfate/Tissue section/Mass spectrometry imaging引用本文复制引用
庄思佳,沈钰琳,杨帆,龚灿,许旭..基于预涂纳米碳-十二烷基硫酸钠复合基质的基质辅助激光解吸电离质谱分析与猪脑组织切片质谱成像[J].分析化学,2024,52(7):985-994,中插22-中插29,18.基金项目
国家自然科学基金项目(No.31671928)和上海应用技术大学科技发展基金项目(No.KJFZ2023-11)资助. Supported by the National Natural Science Foundation of China(No.31671928)and the Science and Technology Development Fund of Shanghai Institute of Technology(No.KJFZ2023-11). （No.31671928）
